Abstract: An image processing device according to an embodiment comprises: a first processing unit for outputting second Bayer data having a second resolution from first Bayer data having a first resolution; a second processing unit for outputting second IR data having a fourth resolution from first IR data having a third resolution; and an image processing unit for outputting a second RGB image by calculating a first RGB image generated from the second Bayer data and an IR image generated from the second IR data.

Abstract: An image processing method for an image processing device according to an embodiment of the present invention comprises the steps of: obtaining a first RGB image by means of an RGB camera; extracting a reflection component from the first RGB image; obtaining a TOF IR image by means of a TOF camera; and obtaining a second RGB image by calculating the reflection component of the first RGB image and the TOF IR image, wherein the TOF IR image is an amplitude or intensity image generated from an IR image with respect to four phases.

Abstract: Disclosed are novel compounds of Chemical Formula 1, optical isomers of the compounds, and pharmaceutically acceptable salts of the compounds or the optical isomers. The compounds, isomers, and salts exhibit excellent activity as GLP-1 receptor agonists. In particular, they, as GLP-1 receptor agonists, exhibit excellent glucose tolerance, thus having a great potential to be used as therapeutic agents for metabolic diseases. Moreover, they exhibit excellent pharmacological safety for cardiovascular systems.

Abstract: A camera device according to an embodiment may include: an image sensor which generates first Bayer data having a first resolution; and a processor which performs deep learning on the basis of the first Bayer data to output second Bayer data having a second resolution higher than the first resolution.

Abstract: A camera according to an embodiment of the present invention comprises: a light-emitting module for configured to output output light according to a set control mode; a light-receiving module configured to receive input light corresponding to the output light according to the control mode; and a control module configured to detect at least one of presence of a subject and a distance from the subject on the basis of the input light, reset the control mode according to a detection result, control an output of the light-emitting module and an input of the light-receiving module according to the reset control mode, and generate a depth map for the subject on the basis of the input light which is input according to the reset control mode.

Abstract: An image processing apparatus and method of extracting a second RGB feature point and a second ToF feature point such that a correlation between the first RGB feature point and the first ToF feature point is equal to or greater than a predetermined value; calculating an error value between the second RGB feature point and the second ToF feature point; updating pre-stored calibration data when the error value is greater than a threshold value, and calibrating the RGB image and the ToF image by using the updated calibration data; and synthesizing the calibrated RGB and ToF images.

Abstract: A camera device according to an embodiment may include: an image sensor which generates first Bayer data having a first resolution; and a processor which performs deep learning on the basis of the first Bayer data to output second Bayer data having a second resolution higher than the first resolution.

Abstract: An auto-focusing method of a camera apparatus according to an embodiment of the present invention comprises the steps of: extracting distance information of an object by using a ToF camera; and performing auto-focusing on an RGB camera by using auto-focusing information according to the distance information, wherein the ToF camera includes an illumination unit for outputting light to the object and a sensor unit for receiving information about light reflected from the object, the sensor unit receives a plurality of pieces of information about the light reflected from the object at a plurality of phases on the basis of the output of the light, and the ToF camera extracts the distance information by using the plurality of pieces of information.

Abstract: A camera device according to an embodiment may comprise an image sensor that generates a first Bayer data having a first resolution, and a processor that outputs a second Bayer data having a second resolution by using the first Bayer data.

Abstract: An image sensor according to one embodiment may comprise: an image sensing unit which receives light and generates a first Bayer pattern having a first resolution; and a processor which receives a second Bayer pattern that is at least a portion of the first Bayer pattern from the image sensing unit, and then generates a third Bayer pattern having a higher resolution than the second alignment unit on the basis of the received second Bayer pattern.

Abstract: An auto-focusing method of a camera apparatus according to an embodiment of the present invention comprises the steps of: extracting distance information of an object by using a ToF camera; and performing auto-focusing on an RGB camera by using auto-focusing information according to the distance information, wherein the ToF camera includes an illumination unit for outputting light to the object and a sensor unit for receiving information about light reflected from the object, the sensor unit receives a plurality of pieces of information about the light reflected from the object at a plurality of phases on the basis of the output of the light, and the ToF camera extracts the distance information by using the plurality of pieces of information.

Abstract: A camera according to an embodiment of the present invention comprises: a light-emitting module for configured to output output light according to a set control mode; a light-receiving module configured to receive input light corresponding to the output light according to the control mode; and a control module configured to detect at least one of presence of a subject and a distance from the subject on the basis of the input light, reset the control mode according to a detection result, control an output of the light-emitting module and an input of the light-receiving module according to the reset control mode, and generate a depth map for the subject on the basis of the input light which is input according to the reset control mode.

Abstract: An image processing method of an image processing apparatus according to an embodiment of the present invention comprises the steps of: obtaining an RGB image from an RGB camera; obtaining a ToF image from a ToF camera; extracting a first RGB feature point from the RGB image; extracting a first ToF feature point from the ToF image; matching the first RGB feature point and the first ToF feature point and extracting a second RGB feature point and a second ToF feature point such that a correlation between the first RGB feature point and the first ToF feature point is equal to or greater than a predetermined value; calculating an error value between the second RGB feature point and the second ToF feature point; updating pre-stored calibration data when the error value is greater than a threshold value, and calibrating the RGB image and the ToF image by using the updated calibration data; and synthesizing the calibrated RGB and ToF images.

Abstract: Disclosed are a sensing method and apparatus, according to one embodiment, which process distance information about a feature point by capturing a pattern image. Specifically, disclosed are a sensing method and apparatus capable of improving the quantity and/or accuracy of information to be sensed, by appropriately realizing repeating shapes of a pattern image.

Abstract: An image processing method for an image processing device according to an embodiment of the present invention comprises the steps of: obtaining a first RGB image by means of an RGB camera; extracting a reflection component from the first RGB image; obtaining a TOF IR image by means of a TOF camera; and obtaining a second RGB image by calculating the reflection component of the first RGB image and the TOF IR image, wherein the TOF IR image is an amplitude or intensity image generated from an IR image with respect to four phases.

Abstract: Disclosed are a camera module and a method of measuring a distance by using the same. The camera module includes a light source to irradiate a light, a film having a pattern through which the light irradiated by the light source passes, an image sensor to acquire an image of a subject, and a distance estimating module to estimate a distance from the subject by using the image acquired by the image sensor. The acquired image includes a pattern image projected by the light passing through the pattern, and the distance estimating module estimates the distance by using the pattern image.

Abstract: Disclosed are a camera module and a method of measuring a distance by using the same. The camera module includes a light source to irradiate a light, a film having a pattern through which the light irradiated by the light source passes, an image sensor to acquire an image of a subject, and a distance estimating module to estimate a distance from the subject by using the image acquired by the image sensor. The acquired image includes a pattern image projected by the light passing through the pattern, and the distance estimating module estimates the distance by using the pattern image.

Abstract: An image processing method and an image processing apparatus are provided. The image processing method includes dividing the image into a plurality of regions; setting a portion of the divided regions to a first region of interest; detecting a candidate region for a target from the first region of interest; determining if the detected candidate region corresponds to the target; detecting a target region by using the candidate region if the candidate region corresponds to the target; estimating a pose of the target by using the detected target region; and performing modeling with respect to the target.

Abstract: An image processing method for detecting a target, includes: an image acquiring unit for acquiring depth information of an image; a histogram creating unit for creating a histogram on the depth information of the image; a critical value setting unit for setting a critical value of the depth information for detecting a region of a detection object from the image; an image processing unit for extracting a region of the detection object from the image by using the set critical value of the depth information; a data verifying unit for verifying whether the extracted region of the detection object corresponds to the target; and a storage unit for storing the extracted region of the detection object. A target is detected based on depth information of an image.

Abstract: A picture control apparatus provides control of a picture displayed on a display of a mobile terminal according to an action detected through image recognition. A picture control method includes detecting an action from images captured by a camera, and controlling a picture displayed on a display if the detected action is a specific action.